A seasonal ARIMA model with exogenous variables for elspot electricity prices in Sweden

Author

Mengchen Xie ; Sandels, C. ; Kun Zhu ; Nordstrom, L.

Author_Institution

Dept. of Math., Univ. of Southern California, Los Angeles, CA, USA

fYear

2013

fDate

27-31 May 2013

Firstpage

1

Lastpage

4

Abstract

In a spot market, price prediction plays an indispensable role in maximizing the benefit of a producer as well as optimizing the utility of a consumer. This paper develops a seasonal ARIMA model with exogenous variables (SARIMAX) to predict day-ahead electricity prices in Elspot market, the largest day-ahead market for power trading in the world. Compared with the basic ARIMA model, SARIMAX has two distinct features: 1) A seasonal component is introduced to cope with weekly effect on price fluctuations. 2) Exogenous variables that exert influence on electricity prices are incorporated to make price predictions in the context of an integrated energy market. A detailed implementation of SARIMAX for Elspot market in Sweden is presented.

Keywords

autoregressive processes; economic forecasting; power markets; pricing; Elspot electricity prices; SARIMAX; Sweden; consumer utility; day-ahead electricity prices; exogenous variables; integrated energy market; price fluctuations; price prediction; price predictions; seasonal ARIMA model; Seasonal ARIMA model; electricity market; exogenous variables; price prediction; time series;

fLanguage

English

Publisher

ieee

Conference_Titel

European Energy Market (EEM), 2013 10th International Conference on the

Conference_Location

Stockholm

Type

conf

DOI

10.1109/EEM.2013.6607293

Filename

6607293